CASIA OpenIR

浏览/检索结果: 共8条,第1-8条 帮助

限定条件        
已选(0)清除 条数/页:   排序方式:
Continuous-Time Time-Varying Policy Iteration 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 12, 页码: 4958-4971
作者:  Wei, Qinglai;  Liao, Zehua;  Yang, Zhanyu;  Li, Benkai;  Liu, Derong
Adobe PDF(3149Kb)  |  收藏  |  浏览/下载:268/50  |  提交时间:2021/03/02
Optimal control  Nonlinear systems  Time-varying systems  Mathematical model  Dynamic programming  Approximation algorithms  Iterative algorithms  Adaptive critic designs  adaptive dynamic programming (ADP)  neuro-dynamic programming  nonlinear systems  optimal control  policy iteration  
Parallel Control for Optimal Tracking via Adaptive Dynamic Programming 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2020, 卷号: 7, 期号: 6, 页码: 1662-1674
作者:  Lu, Jingwei;  Wei, Qinglai;  Wang, Fei-Yue
浏览  |  Adobe PDF(7214Kb)  |  收藏  |  浏览/下载:324/56  |  提交时间:2021/01/06
Adaptive dynamic programming (ADP)  nonlinear optimal control  parallel controller  parallel control theory  parallel system  tracking control  neural network (NN)  
Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 卷号: 50, 期号: 11, 页码: 3959-3971
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  He, Haibo
收藏  |  浏览/下载:168/0  |  提交时间:2021/01/07
Optimal control  Discrete-time systems  Heuristic algorithms  Dynamic programming  Convergence  Artificial intelligence  Nonlinear systems  Adaptive dynamic programming  discrete-time systems  invariant admissibility  optimal control  policy iteration  sum of squares  
Reinforcement Learning-Based Optimal Stabilization for Unknown Nonlinear Systems Subject to Inputs With Uncertain Constraints 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 10, 页码: 4330-4340
作者:  Zhao, Bo;  Liu, Derong;  Luo, Chaomin
收藏  |  浏览/下载:206/0  |  提交时间:2021/01/07
Nonlinear systems  Optimal control  Artificial neural networks  Actuators  Observers  Feedforward systems  Adaptive dynamic programming (ADP)  neural networks (NNs)  optimal control  reinforcement learning (RL)  uncertain input constraints  unknown nonlinear systems  
Discrete-Time Impulsive Adaptive Dynamic Programming 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 10, 页码: 4293-4306
作者:  Wei, Qinglai;  Song, Ruizhuo;  Liao, Zehua;  Li, Benkai;  Lewis, Frank L.
收藏  |  浏览/下载:259/0  |  提交时间:2021/01/07
Optimal control  Performance analysis  Nonlinear systems  Dynamic programming  Heuristic algorithms  Indexes  Adaptive critic designs  adaptive dynamic programming (ADP)  approximate dynamic programming  impulsive control  nonlinear systems  optimal control  
Solving Trajectory Optimization Problems in the Presence of Probabilistic Constraints 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 10, 页码: 4332-4345
作者:  Chai, Runqi;  Savvaris, Al;  Tsourdos, Antonios;  Chai, Senchun;  Xia, Yuanqing;  Wang, Shuo
收藏  |  浏览/下载:183/0  |  提交时间:2021/01/07
Planning  Probabilistic logic  Trajectory optimization  Optimal control  Prediction algorithms  Approximation function  chance-constrained  nonlinear programming  probabilistic constraints  trajectory optimization  
Event-Triggered Adaptive Critic Control Design for Discrete-Time Constrained Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 卷号: 50, 期号: 9, 页码: 3158-3168
作者:  Ha, Mingming;  Wang, Ding;  Liu, Derong
收藏  |  浏览/下载:162/0  |  提交时间:2020/09/28
Nonlinear systems  Actuators  Discrete-time systems  Dynamic programming  Optimal control  Adaptive systems  Adaptive dynamic programming (ADP)  control constraints  event-triggered control  heuristic dynamic programming (HDP)  neural networks  nonlinear discrete-time system  
Optimal Neuro-Control Strategy for Nonlinear Systems With Asymmetric Input Constraints 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2020, 卷号: 7, 期号: 2, 页码: 575-583
作者:  Xiong Yang;  Bo Zhao
浏览  |  Adobe PDF(1346Kb)  |  收藏  |  浏览/下载:132/42  |  提交时间:2021/03/11
Adaptive critic designs (ACDs)  asymmetric input constraint  critic neural network (CNN)  nonlinear systems  optimal control  reinforcement learning (RL)